Disable pre_layer when the model type is not llama

modules/GPTQ_loader.py

@@ -65,8 +65,12 @@ def load_quantized(model_name):
     else:
         model_type = shared.args.model_type.lower()
 
-    if model_type == 'llama' and shared.args.pre_layer:
-        load_quant = llama_inference_offload.load_quant
+    if shared.args.pre_layer:
+        if model_type == 'llama':
+            load_quant = llama_inference_offload.load_quant
+        else:
+            print("Warning: ignoring --pre_layer because it only works for llama model type.")
+            load_quant = _load_quant
     elif model_type in ('llama', 'opt', 'gptj'):
         load_quant = _load_quant
     else:
@@ -107,7 +111,7 @@ def load_quantized(model_name):
         exit()
 
     # qwopqwop200's offload
-    if shared.args.pre_layer:
+    if model_type == 'llama' and shared.args.pre_layer:
         model = load_quant(str(path_to_model), str(pt_path), shared.args.wbits, shared.args.groupsize, shared.args.pre_layer)
     else:
         threshold = False if model_type == 'gptj' else 128